Modeling the Effect of Storage Temperatures on the Growth of Listeria monocytogenes on Ready-to-Eat Ham and Sausage

Luo, Ke; Hong, Sung-Sam; Oh, Deog‐Hwan

doi:10.4315/0362-028x.jfp-15-053

Cited by 16 publications

(11 citation statements)

References 35 publications

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“…As we have also reported, products that received heat treatment (deli meat products and pât e) showed a smaller pathogen incidence than smoked products (Garrido et al 2009). The positive samples found in our study (whipped cream, pork blood sausages, and stew of calf 's foot and cheek) are dairy and meat products, which are considered at risk of L. monocytogenes contamination (Garrido et al 2009;Rebagliati et al 2009;Luo et at., 2015;AESAN, 2010;Rebagliati et al 2009). Of note, all samples of ice cream in our study were negative.…”

Section: Discussionmentioning

confidence: 61%

“…Although food-borne outbreaks of listeriosis remain a major public health problem (Bortolussi, 2008), no enough epidemiological data are available in different countries as Spain or in different types of foods, such as prepared foods, which can may become contaminated due to their origin or their manufacturing process (Luo et al 2015;Bortolussi, 2008).…”

Section: Discussionmentioning

confidence: 99%

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Presence ofListeria monocytogenesin Prepared Foods: Analysis of Influencing Factors

Benito

Figueroa-López²,

Lizana³

et al. 2016

Journal of Food Processing and Preservation

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Although food‐borne outbreaks of listeriosis are uncommon, they remain a major public health problem. We assessed the prevalence of Listeria monocytogenes in prepared foods and the influence of different factors (including type of food or presence of accompanying bacteria). Results showed that accompanying bacteria cause interference in the sensitivity of the detection method, being half Fraser the enrichment medium of choice. In 2760 samples, the global prevalence of L. monocytogenes was 1.4%. In ready‐to‐eat foods, the highest prevalence (23.3%) was found in products containing fermented or cured ingredients and the prevalence was also higher in foods with high counts of aerobic bacteria and lactose‐positive Enterobacteriaceae, two indicators of process hygiene. We also found that foods stored in <0C had a higher prevalence (4.1%) of L. monocytogenes. In prepared foods, factors favoring the presence of L. monocytogenes could be some components of ready‐to‐eat foods, temperatures <0C, and presence of accompanying bacteria. Practical Applications Results are of relevance for practical application as this study was performed in the context of the routine practice of a food control company, with samples collected in different restoration centers from Spain. Results obtained have allowed identifying some factors favoring the presence of L. monocytogenes, which should be taken into account in the current practice of the manufacturing centers of prepared foods to avoid contamination by this bacterium. Based on our results, actions aimed at avoiding high numbers of accompanying bacteria as aerobic mesophilic bacteria (AMB) or Enterobacteriaceae should be taken into account. Special care should also be taken in the manufacturing of foods containing fermented or cured ingredients, as cheese. Finally, the manufacturing centers should also consider the risk of Listeria contamination due to the use of sophisticated machinery or due to the storage of prepared foods at temperatures <0C.

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Section: Discussionmentioning

confidence: 61%

Section: Discussionmentioning

confidence: 99%

Presence ofListeria monocytogenesin Prepared Foods: Analysis of Influencing Factors

Benito

Figueroa-López²,

Lizana³

et al. 2016

Journal of Food Processing and Preservation

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“…Mishra, Guo, Buchanan, Schaffner, and Pradhan () used it to evaluate performance of models for growth of Salmonella and Listeria monocytogenes on leafy greens. Luo, Hong, and Oh () used it to evaluate performance of models for growth of Listeria monocytogenes on RTE ham and sausages. Li et al () used it to evaluate performance of models for thermal inactivation of Listeria innocua in poultry products.…”

Section: Discussionmentioning

confidence: 99%

Predictive model for growth of Salmonella Newport on Romaine lettuce

Oscar

2020

Journal of Food Safety

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Cross‐contamination of ready‐to‐eat (RTE) salad vegetables with Salmonella from raw chicken followed by growth during meal preparation are important risk factors for human salmonellosis. To better predict and manage this risk, a model (general regression neural network) for growth of a chicken isolate of Salmonella Newport (0.91 log) on Romaine lettuce (0.18 g) at times (0–8 hr) and temperatures (16–40°C) observed during meal preparation was developed with Excel, NeuralTools, and @Risk. Model performance was evaluated using the acceptable prediction zones (APZ) method. The proportion of residuals in the APZ (pAPZ) was 0.93 for dependent data (n = 210) and 0.93 for independent data (n = 72) for interpolation. A pAPZ ≥0.70 indicates acceptable model performance. Thus, the model was successfully validated for interpolation and can be used with confidence to predict and manage this important risk to public health.

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“…Comparison of the primary models applied in our study (Table 1) indicated that the logistic model best fitted the experimental results describing the growth of L. monocytogenes in the cooked ham samples. In a similar study, Luo et al (22) modelled the growth kinetics of L. monocytogenes in RTE ham and sausage at temperatures from 4 to 35°C. The observed data fitted four primary models well (the Baranyi, modified Gompertz, logistic, and Huang).…”

Section: Discussionmentioning

confidence: 99%

“…Certain food categories are no longer under a zero tolerance regime but have a specified maximum allowed concentration of 100 CFU/g or ml for products placed on the market during their shelf-life. Therefore, many studies on modelling the effects of various factors on the growth of L. monocytogenes have been published in recent years (5,18,22,23,35). This research allows the behaviour of L. monocytogenes in RTE meat products to be predicted.…”

Section: Discussionmentioning

confidence: 99%

Modelling the growth rate ofListeria monocytogenesin cooked ham stored at different temperatures

Szczawinski

Szczawinska

Łobacz

et al. 2017

Journal of Veterinary Research

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Introduction: The purpose of the study was to determine and model the growth rates of L. monocytogenes in cooked cured ham stored at various temperatures. Material and Methods: Samples of cured ham were artificially contaminated with a mixture of three L. monocytogenes strains and stored at 3, 6, 9, 12, or 15ºC for 16 days. The number of listeriae was determined after 0, 1, 2, 3, 5, 7, 9, 12, 14, and 16 days. A series of decimal dilutions were prepared from each sample and plated onto ALOA agar, after which the plates were incubated at 37ºC for 48 h under aerobic conditions. The bacterial counts were logarithmised and analysed statistically. Five repetitions of the experiment were performed. Results: Both storage temperature and time were found to significantly influence the growth rate of listeriae (P < 0.01). The test bacteria growth curves were fitted to three primary models: the Gompertz, Baranyi, and logistic. The mean square error (MSE) and Akaike's information criterion (AIC) were calculated to evaluate the goodness of fit. It transpired that the logistic model fit the experimental data best. The natural logarithms of L. monocytogenes' mean growth rates from this model were fitted to two secondary models: the square root and polynomial. Conclusion: Modelling in both secondary types can predict the growth rates of L. monocytogenes in cooked cured ham stored at each studied temperature, but mathematical validation showed the polynomial model to be more accurate.

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Modeling the Effect of Storage Temperatures on the Growth of Listeria monocytogenes on Ready-to-Eat Ham and Sausage

Cited by 16 publications

References 35 publications

Presence ofListeria monocytogenesin Prepared Foods: Analysis of Influencing Factors

Presence ofListeria monocytogenesin Prepared Foods: Analysis of Influencing Factors

Predictive model for growth of Salmonella Newport on Romaine lettuce

Modelling the growth rate ofListeria monocytogenesin cooked ham stored at different temperatures

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